Instructions to use ProbeX/Model-J__DINO__model_idx_0912 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__DINO__model_idx_0912 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__DINO__model_idx_0912") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__DINO__model_idx_0912") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0912", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b7b1b1ff2770a417ded0d983b1bac83ddb957417df11c38517d6483b2a455b0
- Size of remote file:
- 343 MB
- SHA256:
- 3c46b4b98e413969691b2db592ed1297b09b279925e4a9676ec2916017d56517
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